Huber loss based distributed robust learning algorithm for random vector functional-link network

In this paper, we propose two algorithms based on the random vector functional link network (RVFLN) and alternating direction method of multipliers algorithm to solve distributed learning (DL) problems with datasets containing outliers. In distributed scenarios, training datasets are separately divi...

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Vydané v:	The Artificial intelligence review Ročník 56; číslo 8; s. 8197 - 8218
Hlavní autori:	Xie, Jin, Liu, Sanyang, Chen, Jiaxi, Jia, Jinping
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Dordrecht Springer Netherlands 01.08.2023 Springer Springer Nature B.V
Predmet:	Algorithms Analysis Artificial Intelligence Communication Communications networks Computational linguistics Computer Science Data mining Datasets Environmental policy Experiments Language processing Learning Machine learning Natural language interfaces Networks Outliers (statistics) Privacy Robustness Vectors (mathematics) Alternating direction method of multipliers Huber loss function Distributed learning Random vector functional link network Distributed robust learning
ISSN:	0269-2821, 1573-7462
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